Beginning My Data Science Journey
Firstly, I should say I lied. I am not at the beginning of my journey, though I am close. However, I need to be stringent. So my journey started in May 2021 (about three months ago) when I enrolled in a master’s in data science. I enrolled in the University of Colorado Boulder’s new Master of Science in Data Science program offered through Coursera. This program is cheaper than most masters options, is fully online, and has a performance-based admissions process. This admissions process was the main reason I chose the program, as I had zero educational experience in data or computer science. My undergraduate degrees were in philosophy and psychology, though I did minor in math. The reader which has followed me thus far may now ask themselves, what led him to choose data science?
I could tell you that I have always been about discovering the truth. I could tell you how I started college in chemistry to discover the ways material objects operate. Or how I switched to philosophy when I wanted to understand how all things operate. Or how I ended my undergraduate career in psychology to understand how my mind operates. Aspects of this may be true; however, the common connection in all these pursuits is that they were and still are of interest to me. Interest is where my pursuit of data science began.
In my last semester of undergrad, I was volunteering as a research assistant in a neuroimaging lab. The main thing that surprised me about this research was how much the professor worked with technology. While he was not operating the fMRI machines, he was constantly working on a couple of computers and operating mainly in the terminal and with a software called FreeSurfer. This in no way matched with my mental image of psychology research in action, clinical or otherwise. However, I was positively intrigued by it. In his lab, the professor’s main job was to propose experiments and explore whether the data generated by the fMRI scans were statistically significant for these experiments. The reason he was constantly on his computer was that fMRI’s produce hundreds of thousands — to millions of data points in a single scanning session. Thus, he spent the majority of his time cleaning and analyzing the data in terms of his experiments.
While this view of psychology highly intrigued me, my experience of it was short-lived. About a third of the way through my semester, on-campus research was shut down due to COVID-19. Thus, I was never able to accomplish too much, but I did leave wanting to learn more and to be better prepared for the field. Hence, I decided to start learning Python, which my professor said would be the most helpful programming language to learn. So I finished the rest of my undergraduate career online and began learning the basics of coding through Codecademy.
In learning Python, my interest in data science began to grow. In Python, the basic syntax, logic flow, and the things that a few keystrokes could accomplish fascinated me. This went even further when I started learning a few general ideas behind machine learning, deep learning, and artificial intelligence. While the ease a computer could handle massively large numbers intrigued me, these advanced concepts seemed almost unreal. I watched the AlphaGo documentary and I built a tiny Tic-Tac-Toe AI. Knowing that these methods and technology could be used to achieve unprecedented and undiscovered results, I decided I wanted to go into technology and specifically data science.
Thus, I continued learning Python and a little bit of SQL and I enrolled at CU Boulder. I have completed four credit hours now and passed the computer science pathway that is one of the options necessary for admissions. Not in one of my classes so far have I used AI or deep learning, but I did learn some nifty algorithms. As I have discovered I was a touch naive to think all a data scientist does is work in deep learning or AI. Some may, but for most data scientists I believe more time is spent with SQL queries.
So I study for classes, I try to better my programming skills in Python, SQL, and R, and I try to learn what being a data scientist is about. I am still looking for an internship or an entry-level role to get in the field, but that will come as I better my skills and try to network a little. I am looking forward to this journey in my life and I am looking forward to writing this blog. Perhaps it may get at least one reader more interested in data science. But at least it will give me an excuse to take some time, reflect, and get my thoughts down.
